Indian community’s Knowledge, Attitude & Practice towards COVID-19

  1. Balvir Singh Tomar
  2. Pratima Singh
  3. Supriya Suman
  4. Preeti Raj
  5. Deepak Nathiya
  6. Sandeep Tripathi
  7. Dushyant Singh Chauhan

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Abstract

As COVID-19 pandemic has caused unprecedented human health consequences. Knowledge, attitude, perception of general population of India towards the transmission and prevention plays vital role for effective control measures. The study was conducted to assess the knowledge, attitude and practice of the general public of India on COVID-19. In this study, a web-based cross-sectional survey was conducted between 10 th March to 18 th April 2020. A 19-item questionnaire was generated, Cronbach’s alpha was used to measure the internal consistency of the questionnaire & randomly distributed among the public using Google forms through social media networks. The chi-square test or Fischer exact test was used to compare categorical data and multiple linear regression was used to identify factor influencing KAP. Among 7978 participants, the overall knowledge, attitude and practice score was 80.64%, 97.33% and 93.8% consecutively. Majority of Indian population demonstrated preceded good knowledge, positive attitude and good practice regarding COVID-19 pandemic.

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  1. ScreenIT

    SciScore for 10.1101/2020.05.05.20092122: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    Institutional Review Board StatementConsent: The cover page of the questionnaire includes a consent form, a declaration of confidentiality, and anonymity.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    Statistical analysis: The data were analysed via statistical Package for the Social Sciences (IBM Corp.
    statistical Package for the Social Sciences
    suggested: None
    IBM SPSS Statistics for Windows, Version 22 Armonk, Chicago,
    SPSS
    suggested: (SPSS, RRID:SCR_002865)

    Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).

    Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:
    Another limitation to the study is limited question in attitude and practice due to limited time for developing questionnaire.

    Results from TrialIdentifier: No clinical trial numbers were referenced.

    Results from Barzooka: We did not find any issues relating to the usage of bar graphs.

    Results from JetFighter: We did not find any issues relating to colormaps.

    Results from rtransparent:
    • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
    • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
    • No protocol registration statement was detected.

    About SciScore

    SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.

  2. Version published to 10.1101/2020.05.05.20092122 on medRxiv